Customer churn. It’s one of the most vexing issues app publishers face as they work to grow their app user base and revenue. The mobile product owners and mobile marketers we know are generally watching app user retention rates very, very closely.

So what can mobile product owners and marketers do — proactively — to impact app retention and customer churn rates for the better?

How about this: What if you could figure out just the right frequency for sending push notifications, so you engage and retain more (lots more) of your app users?

Better yet, what if you could also predict which customers were most likely to churn, so you can take action to try to convince them to stay before they leave for good?

If one or both of those tactics sounds helpful to you, then today’s your lucky day! We’re announcing two new tools we think will help.

The first is data (knowledge is power!) on how push notification send volumes impact app retention rates.

The second is the coming availability of one of our most-requested mobile analytics solutions: Predictive Churn Analytics.

Let’s start with the data.

New Benchmarks Help Answer the FAQ: “How Often Should I Send Push Notifications To Help Prevent Customer Churn?”

As of today, we can add a data-based answer to the question, which might be a surprise to some of you. The answer is: If you’re looking to improve app retention rates, when it comes to push notifications, more is (almost always) better.

Now, before you think we’re recommending that any push notification is a good push notification…we’re definitely not.

What we are saying is that many brands tend to be conservative about the number of push notifications they send, for fear of losing users.

Our data shows, however, that app users who have opted in (or have not opted out) welcome smart (useful, timely, personalized) push notifications — even at (and even especially at) high volumes.

Let’s take a look at the highlights.

Our data scientists pulled and analyzed anonymized data from 63 million app users’ first 90-days in an app. Here are their key findings:

The not-so-great news: 95% of new, opt-in app users churn within the first 90 days if they don’t receive any push notifications.

If they don’t receive messages, only 5% will continue to use the app 90 days after first app open, which means that 95 cents of every dollar spent acquiring them is wasted. (Yikes.)

For Android apps (where users are opted in to receive push notifications as the default setting), 30% of users in our study received no push notifications at all.

On iOS (where users must choose to opt in to receive push notifications), 15% of opt-in users never got a push notification.

The great news: There is a very strong correlation between notification frequency and greater mobile app retention rates.

The more frequently users receive push notifications, the better their retention rates.

App users who receive one or more push notifications in their first 90-days have 190% higher average retention rates than those who don’t receive any push notifications.

While this general pattern of greater frequency equaling greater retention holds true across iOS and Android, there are some variances among different industry verticals, which we’ll share in more about in our upcoming webinar.

Daily or weekly push notifications result in even higher app retention rates.

The most impressive impact on mobile app retention rates was for users who received “Daily +” push notifications.

Apps that sent just over one push notification a day have 90-day app retention rates that are 3X higher on iOS, and 10X higher on Android than users who receive none.

Apps that sent weekly push notifications have 90-day app retention rates that are 2X higher on iOS and 6X higher on Android than users who receive none.

Apps that send “Daily +” push notifications while retaining app users are those that have a strong understanding of their users, and are sending automated, programmatic, targeted push notifications.

If you’re sending a few push notifications, consider how you might start sending personalized, real-time push notifications your users will appreciate at scale. (We can help — schedule a consultation anytime.)

New Predictive Churn Analytics Help You Identify At-Risk Customers — and Take Action to Keep Them

We’ve talked about how you can increase mobile app retention rates by finding the sweet spot for push notification send volume.

Now let’s talk about the fact that the majority of your new app users are still likely to churn.

Even at a Daily + send-level, 54% of opt-in users will churn by month three — as will 85% of your opt-out users. What can you do about them?

In the past, mobile product owners and marketers could try reduce churn by:

Analyzing cohorts to identify higher quality acquisition sources

Retargeting users who had already deleted apps in other channels (although by then it’s a little late..)

Defining an “inactivity” tag or attribute — which really only works if you know with high precision what your customer lifecycle looks like, and all customers behaved the same.

In short, it was rough ideas and best guesses.

As of today, that can change.

Based on a proprietary machine-learning model trained with more than 10 billion data points, our new Predictive Churn analytics solution analyzes user patterns for each app in order to assess a user’s likelihood to churn — before they leave.

It then classifies your app users into three risk profiles: low, medium and high churn risk. These risk profiles allow you to make real-time decisions about the actions you want to take to impact your app retention rate and reduce customer churn.

For example, a coffee retailer might send app users with a low churn risk a push notification with an offer for 10% off; a medium churn risk an offer for 30% off, and a high churn risk a free latte.

And because you can export your mobile analytics to any of your business systems, you can also message users with different risk levels differently on any channel in your stack.

Sound like something you could use in your mobile growth strategy? Predictive Churn is available now as an add-on for Insight, our mobile analytics solution, or for Connect, our mobile data streaming solution.

We hope that the data we’ve shared in this post and in our benchmark report, along with our new Predictive Churn analytics will go a long way to help mobile product owners and mobile marketers reduce customer churn — and make the most out of every dollar spent on app user acquisition.